The analyses described in this paper permitted an evaluation of whether capacity-building professional development practices were related to early childhood intervention practitioners’ reported use of capacity-building family-centered practices. This was ascertained by structural equation modeling for two different types of family-centered practices (participatory and relational) where the two models were compared to determine the better fitting model and the sizes of effects for the relationships among the variables in the models. Results provided converging evidence that capacity-building professional development engenders practitioners’ use of capacity-building family-centered practices. Implications for practice are described.

A sample of 327 engineering bachelor students from a public university in Mexico took part in an information integration study to explore systematic thinking underlying propensity for cheating during a course exam. All study participants were provided with written descriptions of 12 scenarios pertaining to the academic evaluation criteria and were asked to rate the likelihood that they would cheat under such circumstances. The 12 scenarios reflected the experimental manipulation of three orthogonal factors: teacher’s teaching style, type of exam, and modality of assessment. Analysis results revealed four distinct attitudes toward cheating among students, two of which were independent of context (low and high desire to cheat) while the remaining two were context-dependent (low and moderate desire to cheat). All groups showed systematic thinking underlying their possible desire to cheat that was typified by the use of a summative cognitive rule for integrating information related to academic cheating. However, evaluation of factor relevance varied across the groups.

Cheating detection is an important issue in standardized testing, especially in large-scale settings. Statistical approaches are often computationally intensive and require specialised software to conduct. We present a two-stage approach that quickly filters suspected groups using statistical testing on an IRT-based answer-copying index. We also present an approach to mitigate data contamination and improve the performance of the index. The computation of the index was implemented through a modified version of an open source R package, thus enabling wider access to the method. Using data from PIRLS 2011 (N=64,232) we conduct a simulation to demonstrate our approach. Type I error was well-controlled and no control group was falsely flagged for cheating, while 16 (combined n=12,569) of the 18 (combined n=14,149) simulated groups were detected. Implications for system-level cheating detection and further improvements of the approach were discussed.

In the early stages of adopting online learning, both learners and teachers displayed resistance, but the COVID-19 pandemic has forced a widespread shift to digital learning. To facilitate this transition, there is a growing focus on highlighting the effectiveness of online learning, which directly impacts learning outcomes. This study investigates online learning effectiveness through an integrated framework that considers online assessment practices and online course design as independent variables, with online learning support as a moderating variable. Understanding the effectiveness of online learning is crucial as hybrid learning becomes the "new norm" in education, combining online and offline methods for teaching the digital generation. Using a quantitative research design involving 232 students at Universiti Kebangsaan Malaysia, the study found that online assessment practices and course design significantly influence students perceived learning outcomes in an online learning environment. Additionally, online learning support positively moderates this relationship. These findings offer a comprehensive perspective on how online assessment practices, course design, and support systems contribute to the quality of higher education in Malaysia amidst evolving educational practices.